Quantification of Airborne Inoculum as an Aid in the Management of Leaf Blight of Onion Caused by <i>Botrytis squamosa</i>
Bibliographic record
Abstract
Botrytis leaf blight, caused by Botrytis squamosa, is a common and frequently damaging disease of onion crops, but the severity of epidemics varies widely from year to year. The disease is initiated and spread by airborne conidia. The relationship between airborne conidium concentration (ACC) and lesion development was studied in the field. A linear relationship was found between ACC and number of lesions per leaf: ACC values of 10 to 15 and 25 to 35 conidia m-3 were associated with 1 and 2.5 lesions per leaf, respectively. In 2000 and 2001, at three sites, four different criteria were used to start a fungicide spray program and their effect on epidemic development was compared with that of a grower's conventional schedule. The criteria were: at the fourth-true-leaf growth stage; according to an inoculum production index; when the ACC reached 10 to 15 conidia m-3; and when the ACC reached 25 to 35 conidia m-3. A nonsprayed control plot was included in the trial. Fungicide programs started when the ACC reached 10 to 15 conidia m-3 were as effective as the conventional program, but used fewer sprays. A fungicide spray program based on measurements of ACC and disease severity was evaluated in 2002 and 2003 in five and three commercial onion fields, respectively. At each site, half of the field was sprayed according to the grower's schedule and, in the other half, fungicide sprays were initiated when a threshold of 10 to 15 conidia m-3 or five lesions on the lower leaf (whichever came first) was reached. Overall, the number of fungicide applications was reduced by 75 and 56% in 2002 and 2003, respectively, without causing significant yield reduction. In both years, the reduction in number of fungicide applications was due mainly to the delay in initiation of the fungicide program.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".